code: def __init__(self, in_channels=512, pvam_ch=512, char_num=38):
      super(VSFD, self).__init__()
      self.char_num = char_num
      self.fc0 = paddle.nn.Linear(
          in_features=in_channels * 2, out_features=pvam_ch
      )
      self.fc1 = paddle.nn.Linear(
          in_features=pvam_ch, out_features=self.char_num
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  from paddle import nn, ParamAttr
  from paddle.nn import functional
  import numpy
  from .self_attention import WrapEncoderForFeature
  from .self_attention import WrapEncoder
  from paddle.static import Program
  from ppocr.modeling.backbones.rec_resnet_fpn import ResNetFPN
  from collections import OrderedDict
label_desc: Use image node_id 1 to create a new VSFD object from inherited base classes: nn with example: obj = VSFD(in_channels, pvam_ch, char_num)